Mechanistic interpretability is emerging as a strategic advantage for businesses looking to deploy AI responsibly.

"We present dissociative prioritized analysis of dynamics (DPAD), a nonlinear dynamical modeling approach that enables these capabilities with a multisection neural network architecture ... to test ...

The results were published in Neural Networks. Like a river current ... "The brain is difficult to understand, in part, because it is dynamic—it can learn to respond differently to the same stimuli ...

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light instead of electricity to process information—promise faster speeds and ...

Discover the 20 best neural network software. Learn about the features of each software and find the best one. ... One of the key features of MXNet is its dynamic computational graph, ...

These results enable us to design networks that count stimulus pulses, track position, and encode multiple locomotive gaits in a single central pattern generator circuit. Learning Objectives: 1. What ...

A technical paper titled “Map-and-Conquer: Energy-Efficient Mapping of Dynamic Neural Nets onto Heterogeneous MPSoCs” was published (preprint) by researchers at LAMIH/UMR CNRS, Universite ...

SAN FRANCISCO--October 22, 2019-- BrainChip, a leading provider of ultra-low power, high performance edge AI technology, has been awarded a new patent for dynamic neural function libraries, a key ...

Energy and memory: A new neural network paradigm A dynamic energy landscape is at the heart of theorists' new model of memory retrieval Date: May 14, 2025 ...